Universal field matching in craniospinal irradiation by a background-dose gradient-optimized method

Purpose: The gradient-optimized methods are overcoming the traditional feathering methods to plan field junctions in craniospinal irradiation. In this note, a new gradient-optimized technique, based on the use of a background dose, is described. Methods: Treatment planning was performed by RayStation (RaySearch Laboratories, Stockholm, Sweden) on the CT scans of a pediatric patient. Both proton (by pencil beam scanning) and photon (by volumetric modulated arc therapy) treatments were planned with three isocenters. An 'in silico' ideal background dose was created first to cover the upper-spinal target and to produce a perfect dose gradient along the upper and lower junction regions. Using it as background, the cranial and the lower-spinal beams were planned by inverse optimization to obtain dose coverage of their relevant targets and of the junction volumes. Finally, the upper-spinal beam was inversely planned after removal of the background dose and with the previously optimized beams switched on. Results: In both proton and photon plans, the optimized cranial and the lower-spinal beams produced a perfect linear gradient in the junction regions, complementary to that produced by the optimized upper-spinal beam. The final dose distributions showed a homogeneous coverage of the targets. Discussion: Our simple technique allowed to obtain high-quality gradients in the junction region. Such technique universally works for photons as well as protons and could be applicable to the TPSs that allow to manage a background dose

A filtering approach for PET and PG predictions in a proton treatment planning system

Positron emission tomography (PET) and prompt gamma (PG) detection are promising proton therapy monitoring modalities. Fast calculation of the expected distributions is desirable for comparison to measurements and to develop/train algorithms for automatic treatment error detection. A filtering formalism was used for positron-emitter predictions and adapted to allow for its use for the beamline of any proton therapy centre. A novel approach based on a filtering formalism was developed for the prediction of energy-resolved PG distributions for arbitrary tissues. The method estimates PG yields and their energy spectra in the entire treatment field. Both approaches were implemented in a research version of the RayStation treatment planning system. The method was validated against PET monitoring data and Monte Carlo simulations for four patients treated with scanned proton beams. Longitudinal shifts between profiles from analytical and Monte Carlo calculations were within -1.7 and 0.9 mm, with maximum standard deviation of 0.9 mm and 1.1 mm, for positron-emitters and PG shifts, respectively. Normalized mean absolute errors were within 1.2 and 5.3%. When comparing measured and predicted PET data, the same more complex case yielded an average shift of 3 mm, while all other cases were below absolute average shifts of 1.1 mm. Normalized mean absolute errors were below 7.2% for all cases. A novel solution to predict positron-emitter and PG distributions in a treatment planning system is proposed, enabling calculation times of only a few seconds to minutes for entire patient cases, which is suitable for integration in daily clinical routine

Intra-fractional per-beam adaptive workflow to mitigate the need for a rotating gantry during MRI-guided proton therapy

The integration of real-time magnetic resonance imaging (MRI) guidance and proton therapy would potentially improve the proton dose steering capability by reducing daily uncertainties due to anatomical variations. The use of a fixed beamline coupled with an axial patient couch rotation would greatly simplify the proton delivery with MRI guidance. Nonetheless, it is mandatory to assure that the plan quality is not deteriorated by the anatomical deformations due to patient rotation. In this work, an in-house tool allowing for intra-fractional per-beam adaptation of intensity-modulated proton plans (BeamAdapt) was implemented through features available in RayStation. A set of three MRIs was acquired for two healthy volunteers (V1, V2): (1) no rotation/static, (2) rotation to the right and (3) left. V1 was rotated by 15°, to simulate a clinical pediatric abdominal case and V2 by 45°, to simulate an extreme patient rotation case. For each volunteer, a total of four intensity-modulated pencil beam scanning plans were optimized on the static MRI using virtual abdominal targets and two-three posterior-oblique beams. Beam angles were defined according to the angulations on the rotated MRIs. With BeamAdapt, each original plan was initially converted into separate plans with one beam per plan. In an iterative order, individual beam doses were non-rigidly deformed to the rotated anatomies and re-optimized accounting for the consequent deformations and the beam doses delivered so far. For evaluation, the final accumulated dose distribution was propagated back to the static MRI. Planned and adapted dose distributions were compared by computing relative differences between dose-volume histogram metrics. Absolute target dose differences were on average below 1% and organs-at-risk mean dose differences were below 3%. With BeamAdapt, not only intra-fractional per-beam proton plan adaptation coupled with axial patient rotation is possible but also the need for a rotating gantry during MRI guidance might be mitigated